How to include dummy variables in ivreg model in Stata?

[Daniil Yefimov]

I have a model:
ivreg ldemand social_housing transport year (lprice = utilities)
But I want to make year as dummy variable. How can I do it in Stata? i.year doesn't work for ivreg

[Carlo Lazzaro]

Daniil:
I cannot replicate your problem:

use http://www.stata-press.com/data/r15/nlswork

. xtreg ln_w age i.year c.age#c.age tenure not_smsa union south, re

Random-effects GLS regression                   Number of obs     =     19,007
Group variable: idcode                          Number of groups  =      4,134

R-sq:                                           Obs per group:
     within  = 0.1387                                         min =          1
     between = 0.2613                                         avg =        4.6
     overall = 0.2266                                         max =         12

                                                Wald chi2(17)     =    3619.52
corr(u_i, X)   = 0 (assumed)                    Prob > chi2       =     0.0000

------------------------------------------------------------------------------
     ln_wage |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         age |      .0638    .004675    13.65   0.000     .0546372    .0729629
             |
        year |
         71  |   .0122226   .0133882     0.91   0.361    -.0140179    .0384631
         72  |   .0033013   .0131535     0.25   0.802     -.022479    .0290816
         73  |  -.0171295   .0142374    -1.20   0.229    -.0450342    .0107752
         77  |  -.0591987   .0177349    -3.34   0.001    -.0939585    -.024439
         78  |   -.028641   .0198267    -1.44   0.149    -.0675005    .0102186
         80  |  -.0675303   .0224566    -3.01   0.003    -.1115444   -.0235162
         82  |  -.0752261   .0253439    -2.97   0.003    -.1248993    -.025553
         83  |  -.0574366   .0270078    -2.13   0.033    -.1103709   -.0045022
         85  |  -.0248232   .0300102    -0.83   0.408     -.083642    .0339957
         87  |  -.0047382   .0332305    -0.14   0.887    -.0698689    .0603924
         88  |   .0252851   .0355943     0.71   0.477    -.0444785    .0950487
             |
 c.age#c.age |   -.000905   .0000672   -13.47   0.000    -.0010368   -.0007733
             |
      tenure |   .0222127   .0007477    29.71   0.000     .0207472    .0236782
    not_smsa |   -.156615   .0092359   -16.96   0.000     -.174717    -.138513
       union |   .1142884   .0065282    17.51   0.000     .1014933    .1270835
       south |  -.1108392   .0090233   -12.28   0.000    -.1285246   -.0931538
       _cons |    .664906   .0741773     8.96   0.000     .5195212    .8102908
-------------+----------------------------------------------------------------
     sigma_u |  .33168145
     sigma_e |  .25427557
         rho |  .62983588   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. xtivreg ln_w age i.year c.age#c.age not_smsa (tenure = union south), re

G2SLS random-effects IV regression              Number of obs     =     19,007
Group variable: idcode                          Number of groups  =      4,134

R-sq:                                           Obs per group:
     within  = 0.0596                                         min =          1
     between = 0.1780                                         avg =        4.6
     overall = 0.1212                                         max =         12

                                                Wald chi2(15)     =    1017.96
corr(u_i, X)       = 0 (assumed)                Prob > chi2       =     0.0000

------------------------------------------------------------------------------
     ln_wage |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      tenure |     .17626   .0111856    15.76   0.000     .1543367    .1981834
         age |   .0491276   .0087104     5.64   0.000     .0320556    .0661996
             |
        year |
         71  |  -.0316701    .027218    -1.16   0.245    -.0850164    .0216762
         72  |  -.0252266   .0259762    -0.97   0.331     -.076139    .0256858
         73  |  -.0761155   .0276047    -2.76   0.006    -.1302197   -.0220113
         77  |  -.1561267   .0291789    -5.35   0.000    -.2133162   -.0989373
         78  |  -.1898602   .0338453    -5.61   0.000    -.2561957   -.1235248
         80  |  -.1867523   .0346128    -5.40   0.000    -.2545921   -.1189125
         82  |   -.264212   .0379957    -6.95   0.000    -.3386823   -.1897417
         83  |  -.3274644   .0421063    -7.78   0.000    -.4099912   -.2449376
         85  |   -.293698   .0444716    -6.60   0.000    -.3808608   -.2065353
         87  |  -.3123237   .0481168    -6.49   0.000    -.4066308   -.2180166
         88  |  -.4193996   .0556621    -7.53   0.000    -.5284953   -.3103039
             |
 c.age#c.age |  -.0010334     .00013    -7.95   0.000    -.0012882   -.0007787
             |
    not_smsa |  -.2082097   .0131004   -15.89   0.000    -.2338859   -.1825334
       _cons |    .903967   .1323148     6.83   0.000     .6446347    1.163299
-------------+----------------------------------------------------------------
     sigma_u |  .33970135
     sigma_e |  .61262621
         rho |  .23516437   (fraction of variance due to u_i)
------------------------------------------------------------------------------
Instrumented:   tenure
Instruments:    age 71.year 72.year 73.year 77.year 78.year 80.year 82.year
                83.year 85.year 87.year 88.year c.age#c.age not_smsa union
                south
------------------------------------------------------------------------------

.

[Nick Cox]

Cross-posted at https://stackoverflow.com/questions/...in-ivreg-model

Please note our policy on cross-posting (FAQ Advice #8), which is that you are asked to tell us about it. https://www.statalist.org/forums/help#crossposting

[Carlo Lazzaro]

Daniil:
in my previous post I've misread -ivreg- for -xtivregress-.
Tracking down some details, I've noticed that -ivreg-, that dates back to Stata 10 (by the way: if you're using that release, as per FAQ you should have made explicit in your post), has been replaced by -ivregress-.
Being a bit old-fashioned. -ivreg- does not allow -fvvarlist- notation (and some other options which are instead available with -ivregress-).
However, the usual -xi:- trick can work this nuisance around, as you can see from the following toy-example:

webuse hsng2

. xi: ivreg rent pcturban (hsngval = faminc i.region)
i.region          _Iregion_1-4        (naturally coded; _Iregion_1 omitted)

Instrumental variables (2SLS) regression

      Source |       SS           df       MS      Number of obs   =        50
-------------+----------------------------------   F(2, 47)        =     42.66
       Model |  36677.4033         2  18338.7017   Prob > F        =    0.0000
    Residual |  24565.7167        47  522.674823   R-squared       =    0.5989
-------------+----------------------------------   Adj R-squared   =    0.5818
       Total |    61243.12        49  1249.85959   Root MSE        =    22.862

------------------------------------------------------------------------------
        rent |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     hsngval |   .0022398   .0003388     6.61   0.000     .0015583    .0029213
    pcturban |    .081516   .3081528     0.26   0.793    -.5384074    .7014394
       _cons |   120.7065   15.70688     7.68   0.000     89.10834    152.3047
------------------------------------------------------------------------------
Instrumented:  hsngval
Instruments:   pcturban faminc _Iregion_2 _Iregion_3 _Iregion_4
------------------------------------------------------------------------------

.